A real-time image captioning framework using computer vision to help the visually impaired
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-17849-7.pdf
Reference45 articles.
1. Tiwary T, Mahapatra RP (2023) An accurate generation of image captions for blind people using extended convolutional atom neural network. Multimed Tools Appl 82:3801–3830. https://doi.org/10.1007/s11042-022-13443-5
2. Chu Y, Yue X, Lei Y, Sergei M, Wang Z (2020) Automatic Image Captioning Based on ResNet50 and LSTM with Soft Attention. Wirel Commun Mob Comput 2020:8909458–7. https://doi.org/10.1155/2020/8909458
3. Liu Z et al (2021) Swin transformer: hierarchical vision transformer using shifted windows. In 2021 IEEE/CVF International Conference on Computer Vision (ICCV), Montreal, QC, Canada, p 9992–10002. https://doi.org/10.1109/ICCV48922.2021.00986
4. de Freitas MP, Piai VA, Farias RH, Fernandes AMR, de MoraesRossetto AG, Leithardt VRQ (2022) Artificial intelligence of things applied to assistive technology: A systematic literature review. Sensors (Basel) 22(21):8531. https://doi.org/10.3390/s22218531
5. Feng J, Zhao J (2022) Context-fused guidance for image captioning using sequence-level training. Comput Intell Neuroscie 9743123:9. https://doi.org/10.1155/2022/9743123
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